The battle over customer versus internal business processes requirements and priorities has been fought — and the internal processes lost. Game over. Customers are now empowered with mobile devices and ubiquitous cloud-based all-but-unlimited access to information about products, services, and prices. Customer stickiness is extremely difficult to achieve as customers demand instant gratification of their ever changing needs, tastes, and requirements, while switching vendors is just a matter of clicking a few keys on a mobile phone. Forrester calls this phenomenon the age of the customer. The age of the customer elevates business and technology priorities to achieve:

Business agility. Forrester consistently finds one common thread running through the profile of successful organizations — the ability to manage change. In the age of the customer, business agility often equals the ability to adopt, react, and succeed in the midst of an unending fountain of customer driven requirements. Forrester sees agile organizations making decisions differently by embracing a new, more grass-roots-based management approach. Employees down in the trenches, in individual business units, are the ones who are in close touch with customer problems, market shifts, and process inefficiencies. These workers are often in the best position to understand challenges and opportunities and to make decisions to improve the business. It is only when responses to change come from within, from these highly aware and empowered employees, that enterprises become agile, competitive, and successful.

Information agility. Agile enterprises must gather customer and market knowledge and rapidly incorporate it into decisions. In order to support and promote business agility, enterprise knowledge workers need to be empowered with easy access to agile, flexible, and responsive enterprise business intelligence tools and applications. However, while organizations of all sizes made significant headway over the last several decades in their enterprise BI accomplishments, many organizations still struggle with making their data and information management, BI, and analytics environments agile.

Alas, enterprise grade BI platforms are often anything but agile. Indeed, all modern enterprise BI platforms are scalable and robust, support and promote a single version of the truth, and minimize operational risk. However, these capabilities carry a hefty price tag of complexity, rigidity, and inflexibility, and as a result they are slow to react to constantly changing customer and business requirements. This lack of BI agility promotes an unfortunate side effect — proliferation of shadow IT, “homegrown” BI applications”

A word of caution: Do not use the term Agile BI synonymously with the terms intuitive and user friendly — two hugely overused and hyped terms in BI. Unfortunately, these terms are highly subjective and qualitative. Point-and-click, drag-and-drop GUIs may be intuitive to an experienced professional with a background in command line interfaces, but not so obvious to a millennial who grew up with a thumb-typing mobile phone UI. And while menu- and prompt-driven instrumented (radio buttons, dialog boxes, etc.) applications may seem user friendly to left-brained people (who think in numbers and lists), right-brained office workers (who see the world in pictures and associations) may prefer an application driven by icons, visual associations, and artistic Infographics.

While mainly academic discussion of these terms may be thought-provoking, it’s not really actionable. Forrester takes a more pragmatic and practical approach and describes Agile BI in highly objective and quantifiable terms, which specifically address many of the shortcomings and limitations (rigid and restrictive data models, too much reliance on technology management professionals, and many others) of the traditional enterprise BI platforms, including platform features such as

IT-enabled BI self-service. What are the BI platform features that enable technology professionals to empower business user self-service capabilities? These features include cascading parameters and nested prompts, collaboration, data virtualization and drill anywhere, parameterized reporting, prompt for columns, migration of user-sandbox-generated BI content to production, and write back.

BI automation. Does the BI platform support various self-service BI automation processes that allow business users to do more with less? Beyond commoditized and non-differentiated features like report batches, report scheduling, etc., these features should include such capabilities as auto information discovery, actionable BI, contextual BI, suggestive BI, and managing a full BI life cycle with a single integrated development environment (IDE).

Additionally, Agile BI requires capabilities that empower business users to be self-sufficient in their BI environment with little or no involvement from technology professionals. These capabilities are typically supported by BI platform features such as:

Self-provisioning applications and data. How efficiently can business users connect to new data sources and provision applications, data, and resources? This includes such capabilities as application sandboxes, data upload, data virtualization and drill anywhere, elasticity, semantic layer, and mobile delivery.

Effective user interfaces. How easily can business users create their own reports and dashboards and run data exploration and other relevant tasks? Going beyond highly commoditized and nondifferentiated graphical user interface (GUI) features like point-and-click and drag-and-drop, this criteria includes capabilities such as collaboration, data exploration and discovery, faceted navigation, guided navigation, information workplace integration, natural language processing (NLP), and search like GUI.

Last but not least, Agile BI requires rich advanced data visualization (ADV) capabilities. Older definitions of ADV (versus static data graphs and charts) included visual querying (without writing SQL code), dynamic visualizations (where visualizations dynamically changed based on query results), and several others. These features, however, are table stakes in all modern BI platforms and no longer differentiate one vendor from another. Today we look for differentiated ADV capabilities such as:

Richness of ADV content. What are the BI platform ADV capabilities in terms of richness of data visualization content like graphs and charts that are available out of the box? Includes such capabilities as cockpit gauges, custom charts and maps, geospatial representations, and infographics.

Data visualization effectiveness. What are the BI platform ADV capabilities in terms of allowing business users to efficiently and effectively visualize data sets and act on the results? This includes capabilities such as animations, autosuggestions, modes of interaction, multiple dimensions, and storyboarding. Autosuggestions is a top differentiator in ADV these days. Look for capabilities to help the user select the best possible visualization or chart type. Can the system analyze the input data, recognize the pattern and key field, and automatically propose a ‘best practice’ visualization for an individual data set?

Comments

A company that uses algorithms developed for processing the data created as part of the CERN project for predictive modelling, regularly posts updates on its work and developments in Data strategy ecosphere.

The clunkiness of enterprise grade BI platforms maybe down to having to mine data from a combination of legacy systems. In the future, I believe we’ll see BI becoming more agile as smarter middleware enables a more rapid querying of disparate system sources. And although you are right that “agile” should not be synonymous with “user friendly” there is no question that most BI systems could use a UX overhaul. However smart the data, if people can’t get to it, it’s useless.

"These workers are often in the best position to understand challenges and opportunities and to make decisions to improve the business. "

Exactly! The closer your employees are to your customers the better they understand their real wants and needs. What are their complaints? What are their concerns? What are their questions? These people need the data analysis that BI systems can give them to better answer questions.